KrkNLO matching and phenomenology for vector boson processes

TL;DR

This paper extends and validates the KrkNLO NLO matching method within Herwig for vector boson processes at the LHC, demonstrating its effectiveness in eliminating negative weights and comparing favorably with other methods and experimental data.

Contribution

It presents the full implementation of the KrkNLO method for vector boson processes in Herwig, including validation and detailed comparison with other matching schemes and LHC data.

Findings

KrkNLO effectively eliminates negative weights in NLO event generation.

The method shows good agreement with LHC data across multiple processes.

Comparison with MC@NLO highlights differences in phase-space predictions.

Abstract

The combination of NLO matrix elements with parton showers is indispensable for LHC physics. Differences between matching methods introduce matching uncertainties, corresponding to formally higher-order terms. We recently presented the process-independent generalisation of the KrkNLO method for NLO matching, which employs a modified PDF factorisation scheme to achieve NLO accuracy. With this factorisation scheme, the method can be used for colour-singlet final-states, and was previously implemented in the Herwig Monte Carlo Event Generator and applied to the diphoton-production process. Here we present the extension of the implementation of the KrkNLO method within Herwig to support the full class of applicable processes, using an external matrix-element library. We re-validate the implementation, and use it to study the NLO matching uncertainty for four vector-boson production processes at the LHC: $W$, $Z\gamma$, $WW$ and $ZZ$. We demonstrate that the KrkNLO method effectively eliminates the negative-weight problem in NLO event generation, across the four processes studied. We provide detailed comparisons between KrkNLO and variants of the MC@NLO method with different shower starting-scale choices, across processes and throughout phase-space, including double-differential observables. For each process, we compare the predictions to LHC data from ATLAS.